117 citations · 488 across the 32 of their papers we have counts for
35 papers
Towards an Extensible Benchmark for Spoken Dialogue with Social Robots
Casey Kennington, Ross Mead, Saad Elbeleidy +1
Language models provide a plug-and-play interface between humans and robots, but important challenges remain when speech, dialogue, fast interaction, and collaboration are required…
ViSaRL: Visual Reinforcement Learning Guided by Human Saliency
Anthony Liang, Jesse Thomason, Erdem Bıyık
Training robots to perform complex control tasks from high-dimensional pixel input using reinforcement learning (RL) is sample-inefficient, because image observations are comprised…
Exploring Strategies for Modeling Sign Language Phonology
Lee Kezar, Riley Carlin, Tejas Srinivasan +3
Like speech, signs are composed of discrete, recombinable features called phonemes. Prior work shows that models which can recognize phonemes are better at sign recognition, motiva…
Chain-of-Questions Training with Latent Answers for Robust Multistep Question Answering
Wang Zhu, Jesse Thomason, Robin Jia
We train a language model (LM) to robustly answer multistep questions by generating and answering sub-questions. We propose Chain-of-Questions, a framework that trains a model to g…
I2I: Initializing Adapters with Improvised Knowledge
Tejas Srinivasan, Furong Jia, Mohammad Rostami +1
Adapters present a promising solution to the catastrophic forgetting problem in continual learning. However, training independent Adapter modules for every new task misses an oppor…
Task-Attentive Transformer Architecture for Continual Learning of Vision-and-Language Tasks Using Knowledge Distillation
Yuliang Cai, Jesse Thomason, Mohammad Rostami
The size and the computational load of fine-tuning large-scale pre-trained neural network are becoming two major obstacles in adopting machine learning in many applications. Contin…